基於無線腦機介面之創新運動想像分類演算法

Abstract

腦機介面(Brain computer interface, BCI)是大腦和電腦或其他裝置之間一個有效的溝通方式。很多生理訊號都可以用於操作腦機介面。而其中，運動想像(Motor imagery, MI)已被證明是操作腦機介面的一個有效方式。近來，有很多關於使用運動想像操作腦機介面的研究。在這些研究當中，很常有正確率不高無法正確辨認使用者的操作指令以及計算時間太長導致系統反應較慢的問題。這篇研究提出一個新的演算法可以同時提高分類正確率和維持系統的計算效率。而正確率高又有效率的系統很適合用於日常生活中即時的腦機介面系統的應用裝置。以外，本研究將此演算法應用在無線可攜式腦機介面Mindo上，使得運動想像腦機介面距離日常生活更進一步。

Brain computer interface (BCI) is known as a good way to communicate between brain and computer or other device. There are many kinds of physiological signal can operate BCI systems. Motor imagery (MI) has been demonstrated to be a good way to operate a BCI system. In some recent studies about MI based BCI systems, low accuracy rate and time consuming are common problems. In this study, a novel motor imagery algorithm is proposed to improve the accuracy rate and computational efficiency at the same time. This novel algorithm with high accuracy rate and efficiency can be applied to real time BCI system in real-life applications. In addition, this study applies the algorithm on a portable wireless BCI system – Mindo, makes BCI more closer to daily life.